Data sharding for transmission over a high generation cellular network

ABSTRACT

Aspects of the disclosure relate to data sharding for transmission over a high generation cellular network. A computing platform may detect, via a communication network, transmission of data from a first computing device to a second computing device. Subsequently, the computing platform may intercept, prior to receipt of the transmission by the second computing device, the data. Then, the computing platform may shard the data into a first shard and a second shard. Then, the computing platform may identify, within the communication network, a first communication channel and a second communication channel. Then, the computing platform may send, to the second computing device, the first shard via the first communication channel, and the second shard via the second communication channel. Subsequently, the computing platform may merge, the first shard and the second shard, to reconfigure the data.

This application claims the benefit of and is a continuation of U.S.patent application Ser. No. 16/778,513, filed Jan. 31, 2020, andentitled “Data Sharding for Transmission over a High Generation CellularNetwork,” This application is incorporated by reference herein in itsentirety.

BACKGROUND

Aspects of the disclosure relate to deploying digital data processingsystems to real-time protection of data. In particular, one or moreaspects of the disclosure relate to data sharding for transmission overa high generation cellular network.

Enterprise organizations may utilize various resources to support theircomputing infrastructure. For large enterprise organizations,maintaining, updating, and managing network activity over the variousenterprise resources may be of significant importance in protectingconfidential information and/or other sensitive data that is created,transmitted, and/or used for various purposes. It may be helpful tointercept data flow between servers, applications, devices, and soforth, to streamline data transmission, and protect data in transit. Asdata flows through the network in real-time, such detection andmanagement of data may be time-sensitive and there may be significantadvantages for the data protection to be performed in real-time as well.Ensuring that data integrity is maintained, and timely and targetedpreventive measures are undertaken, in real-time with speed andaccuracy, may be particularly advantageous to ensure a smooth running ofan enterprise infrastructure. In many instances, however, it may bedifficult to analyze and/or protect data transmission, in anorganization's complex network comprising a vast number of networkdevices and users, while also attempting to optimize network resources,bandwidth utilization, and efficient operations of the computinginfrastructure.

SUMMARY

Aspects of the disclosure provide effective, efficient, scalable, fast,reliable, and convenient technical solutions that address and overcomethe technical problems associated with data transmission in real-time,by utilizing a high generation cellular network.

In accordance with one or more embodiments, a computing platform havingat least one processor, and memory may detect, via a communicationnetwork, transmission of data from a first computing device to a secondcomputing device. Subsequently, the computing platform may intercept,prior to receipt of the transmission by the second computing device, thedata. Then, the computing platform may shard the data into a first shardand a second shard. Then, the computing platform may identify, withinthe communication network, a first communication channel and a secondcommunication channel. Then, the computing platform may send, to thesecond computing device, the first shard via the first communicationchannel, and the second shard via the second communication channel.Subsequently, the computing platform may merge, the first shard and thesecond shard, to reconfigure the data.

In some embodiments, the transmission of data may include encrypteddata, and the first shard may include the encrypted data, and the secondshard may include encryption key management data associated with theencrypted data. In some embodiments, the data may include trading data,and the computing platform may identify, from the trading data,non-confidential data and confidential data. Then, the computingplatform may identify, within the communication network, a thirdcommunication channel. Then, the computing platform may encrypt theconfidential data. In some embodiments, the encrypted data may includethe encrypted form of the confidential data. Subsequently, the computingplatform may send the non-confidential data via the third communicationchannel.

In some embodiments, the first communication channel may be over aprivate enterprise network, and the second communication channel may beover a public network.

In some embodiments, the computing platform may determine that a size ofthe data exceeds a threshold. Then, the computing platform may shard thedata to limit a size of each of the first shard and the second shard toless than the threshold.

In some embodiments, the first communication channel and the secondcommunication channel may be over a fifth-generation cellular network.In some embodiments, the first communication channel may be associatedwith a first frequency for data transmission, and the secondcommunication channel may be associated with a second frequency for datatransmission. In some embodiments, the first communication channel maybe over a private enterprise network of the fifth-generation cellularnetwork, and the second communication channel may be over a publicnetwork of the fifth-generation cellular network.

In some embodiments, the computing platform may include a transceiver,and the computing platform may, prior to sending the first shard and thesecond shard, configure the transceiver to convert the first shard andthe second shard into a format compatible with data transmission overthe cellular network.

These features, along with many others, are discussed in greater detailbelow.

BRIEF DESCRIPTION OF THE DRAWINGS

The present disclosure is illustrated by way of example and not limitedin the accompanying figures in which like reference numerals indicatesimilar elements and in which:

FIGS. 1A and 1B depict an illustrative computing environment for datasharding for transmission over a high generation cellular network inaccordance with one or more example embodiments;

FIG. 2 depicts an illustrative network environment for data sharding fortransmission over a high generation cellular network in accordance withone or more example embodiments;

FIG. 3 depicts another illustrative network environment for datasharding for transmission over a high generation cellular network inaccordance with one or more example embodiments;

FIG. 4 depicts an illustrative method for data sharding for transmissionover a high generation cellular network in accordance with one or moreexample embodiments; and

FIG. 5 depicts another illustrative method for data sharding fortransmission over a high generation cellular network in accordance withone or more example embodiments.

DETAILED DESCRIPTION

In the following description of various illustrative embodiments,reference is made to the accompanying drawings, which form a parthereof, and in which is shown, by way of illustration, variousembodiments in which aspects of the disclosure may be practiced. It isto be understood that other embodiments may be utilized, and structuraland functional modifications may be made, without departing from thescope of the present disclosure.

It is noted that various connections between elements are discussed inthe following description. It is noted that these connections aregeneral and, unless specified otherwise, may be direct or indirect,wired or wireless, and that the specification is not intended to belimiting in this respect.

Some aspects of the disclosure relate to data sharding for transmissionover a high generation cellular network. For example, an enterprisenetwork management infrastructure may deploy computing resources such asnetwork devices, web resources, electronic mail applications, externalvendor applications, mobile applications, and so forth. A large amountof data (including machine-generated data) may be exchanged between suchapplications, both within an enterprise organization, and betweenexternal entities and entities within the enterprise organization. Insome instances, such data transmissions, unless adequately protected,may pose a large security threat to the enterprise services. For largeenterprise organizations with vast amounts of deployed resources and alarge number of employees, data transmissions may take varied andcomplex forms, and it may be advantageous to provide real-timeprotection, including protecting in transit.

Cellular networks are generally associated with service areas that aresubdivided into cells. Location data for a device is based on the cellwithin which the device is located. Accordingly, smaller cells providegreater accuracy and reliability of location data. High generationcellular networks, such as a fifth generation (“5G”) cellular network,may be configured to considerably reduce the cell size, therebyimproving accuracy of location data. Also, for example, in highgeneration cellular networks, each cell may be equipped with multipleantennas configured to communicate with a computing device within thecell so that multiple streams of data may be simultaneously transmitted,thereby increasing data transmission rates, reducing backlog due tonetwork traffic, and enhancing speed and accuracy of communications.Multiple streams, often with prescribed frequency bandwidths, may alsoenable more efficient transmission of data.

Also, the ability to establish and maintain a reliable communicationchannel between computing devices sharing data may be useful inmaintaining integrity of data transmissions. When time-sensitive datahas to be identified, processed and shared in real-time, high-speed datatransmission rates, increased bandwidth, and low latency may be of greatsignificance to transmit data with speed and accuracy, while maintainingthe integrity and confidentiality of the underlying data.

Generally, it may not be possible to manually manage such a vast arrayof network applications and devices, with near-continuous flow of data.Accordingly, it may be of great significance for a large enterpriseorganization (e.g., financial institution), with large amounts ofconfidential information to protect, to detect and protect, inreal-time, data transmissions.

Accordingly, aspects of this disclosure relate to automated monitoringof data transmissions between a source computing device and adestination computing device and protect such data transmissions inreal-time. Intercepting, and/or protecting such data transmissions via amanual process and/or based on mental steps is unlikely because itrelates to vast amounts of real-time data traffic, and such data trafficis rapidly changing in real-time over thousands of enterprise resources.Also, since the data may reside and/or be exchanged over a vast array ofusers, internal and external applications, and network devices, itnecessitates a use of computing devices to intercept the plurality ofdata transmissions over networks, shard the data when appropriate,identify appropriate wireless network channels to send the sharded data,and merge the shards to reconfigure the data, in real-time and over thenetwork.

In many enterprise related applications, networks may experiencebottlenecks and other data traffic congestion issues. Limits on storagecapacities, memory capacities, available processing capacities for CPUs,and network bandwidth related issues, may contribute to such trafficcongestion. Accordingly, data sharding may be an effective way toalleviate some of the technical challenges encountered in datatransmissions. Also, for example, financial institutions handle largevolumes of confidential data. Such data may need to be encrypted.However, encrypted data may be intercepted in transmission, and may beexposed to a risk of being decrypted. In some instances, such a risk maybe minimized by separating the encrypted data traffic and the keymanagement traffic, as described herein. It may be noted, that as datatransmissions occur over a computing network, the problem of protectingdata transmissions arises in the realm of networks, and as describedherein, a solution is necessarily rooted in computer technology toovercome a problem arising in the realm of computer networks.

FIGS. 1A and 1B depict an illustrative computing environment for datasharding for transmission over a high generation cellular network inaccordance with one or more example embodiments. Referring to FIG. 1A,computing environment 100 may include one or more computer systems. Forexample, computing environment 100 may include data sharding computingplatform 110, enterprise network management infrastructure 120,enterprise data storage platform 130, first computing device 140, secondcomputing device 150, transceiver 160, and external computing device170.

As illustrated in greater detail below, data sharding computing platform110 may include one or more computing devices configured to perform oneor more of the functions described herein. For example, data shardingcomputing platform 110 may include one or more computers (e.g., laptopcomputers, desktop computers, servers, server blades, or the like)and/or other computer components (e.g., processors, memories,communication networks).

Enterprise network management infrastructure 120 may include one or morecomputing devices and/or other computer components (e.g., processors,memories, communication interfaces). In addition, enterprise networkmanagement infrastructure 120 may be configured to manage, host,execute, and/or otherwise provide one or more enterprise applicationsand/or devices (e.g., first enterprise computing device 140, secondenterprise computing device 150). For example, enterprise networkmanagement infrastructure 120 may be configured to manage, host,execute, and/or otherwise provide a computing platform for variousnetwork devices and enterprise applications. In some instances,enterprise network management infrastructure 120 may be configured toprovide various enterprise and/or back-office computing functions for anenterprise organization, such as a financial institution. For example,enterprise network management infrastructure 120 may include variousservers and/or databases that store and/or otherwise maintain accountinformation, such as financial account information including accountbalances, transaction history, account owner information, and/or otherinformation. Also, for example, enterprise network managementinfrastructure 120 may include various servers and/or databases that maymanage information technology resources for the enterprise organization.Additionally, or alternatively, enterprise network managementinfrastructure 120 may receive instructions from data sharding computingplatform 110 and execute the instructions in a timely manner.

Enterprise data storage platform 130 may include one or more computingdevices and/or other computer components (e.g., processors, memories,communication interfaces). In addition, and as illustrated in greaterdetail below, enterprise data storage platform 130 may be configured tostore and/or otherwise maintain enterprise data, including dataexchanged between network devices and/or other resources hosted,executed, and/or otherwise provided by enterprise network managementinfrastructure 120. Also, for example, enterprise data storage platform130 may be configured to store and/or otherwise maintain informationassociated with data transmissions between enterprise applicationsand/or devices (e.g., first enterprise computing device 140, secondenterprise computing device 150), and/or between an enterpriseapplication and/or device and an external vendor application, usercomputing device (e.g., first enterprise computing device 140 andexternal computing device 170). Additionally, or alternatively,enterprise network management infrastructure 120 may load data fromenterprise data storage platform 130, manipulate and/or otherwiseprocess such data, and return modified data and/or other data toenterprise data storage platform 130 and/or to other computer systemsincluded in computing environment 100.

First enterprise computing device 140 and second enterprise computingdevice 150 may be devices, servers, and so forth configured to hostapplications utilized by the enterprise organization, and managed,hosted, executed, and/or otherwise provided by enterprise networkmanagement infrastructure 120. For example, first enterprise computingdevice 140 may host a financial application and second enterprisecomputing device 150 may host an accounting application. Also, forexample, first enterprise computing device 140 may host a travelreservation related application and second enterprise computing device150 may host an expense management application. Also, for example, firstenterprise computing device 140 may host a word processing applicationand second enterprise computing device 150 may host a telecommunicationsapplication. In some embodiments, first enterprise computing device 140and second enterprise computing device 150 may be user devices thatexchange data, and/or user devices that access enterprise applications.The term “enterprise application” as used herein, may generally refer toany application used within an enterprise organization. For example, anenterprise application may be a stand-alone application, or a suite ofapplications.

External computing device 170 may be a device, server, and so forthconfigured to host an application provided by a vendor, and/or a useroutside the enterprise organization. For example, external computingdevice 170 may host a human resource application, a travel managementapplication, a health insurance provider application, payment processingapplication, a voice over IP (“VOIP”) service application, and so forth.The term “external application” as used herein, may generally refer toany application provided by an external vendor to an enterpriseorganization. In some embodiments, external computing device 170 may bea user device that may communicate with first enterprise computingdevice 140 and/or second enterprise computing device 150. For example,external computing device 170 may be a user device that communicateswith a web portal for a financial institution.

Transceiver 160 may be a device, server, and so forth configured toformat data for receipt and transmission over a cellular network. Forexample, transceiver 160 may be an antenna that communicates databetween an enterprise organization's private network and a cellularnetwork's transmission antenna. Also, for example, transceiver 160 maybe an antenna that communicates data between a mobile computing deviceand a cellular network's transmission tower.

Computing environment 100 also may include one or more networks, whichmay interconnect one or more of data sharding computing platform 110,enterprise network management infrastructure 120, enterprise datastorage platform 130, first enterprise computing device 140, secondenterprise computing device 150, transceiver 160, and external computingdevice 170. For example, computing environment 100 may include privatenetwork 180 (which may interconnect, for example, data shardingcomputing platform 110, enterprise network management infrastructure120, enterprise data storage platform 130, first enterprise computingdevice 140, second enterprise computing device 150, transceiver 160,and/or one or more other systems (which may be associated with anorganization, such as a financial institution), and public network 190(which may interconnect, for example, external computing device 170 withprivate network 180 and/or one or more other systems, public networks,sub-networks, and/or the like). For example, public network 190 mayinterconnect external computing device 170 with first enterprisecomputing device 140 and/or second enterprise computing device 150 viaprivate network 180. In some instances, public network 190 may be a highgeneration cellular network, such as, for example, a fifth generation(“5G”) or higher cellular network. In some instances, private network180 may likewise be a high generation cellular enterprise network, suchas, for example, a 5G or higher cellular network. In some embodiments,private network 180 may be a 5G network privately owned and/or licensedby an enterprise organization.

In one or more arrangements, data sharding computing platform 110,enterprise network management infrastructure 120, enterprise datastorage platform 130, first enterprise computing device 140, secondenterprise computing device 150, transceiver 160, and external computingdevice 170, and/or the other systems included in computing environment100 may be any type of computing device capable of communicating with auser interface, receiving input via the user interface, andcommunicating with one or more other computing devices. For example,data sharding computing platform 110, enterprise network managementinfrastructure 120, enterprise data storage platform 130, firstenterprise computing device 140, second enterprise computing device 150,transceiver 160, and external computing device 170, and/or the othersystems included in computing environment 100 may, in some instances, beand/or include server computers, desktop computers, laptop computers,tablet computers, smart phones, or the like that may include one or moreprocessors, memories, communication interfaces, storage devices, and/orother components. As noted above, and as illustrated in greater detailbelow, any and/or all of data sharding computing platform 110,enterprise network management infrastructure 120, enterprise datastorage platform 130, first enterprise computing device 140, secondenterprise computing device 150, transceiver 160, and external computingdevice 170, may, in some instances, be special-purpose computing devicesconfigured to perform specific functions.

Referring to FIG. 1B, data sharding computing platform 110 may includeone or more processors 111, memory 112, and communication interface 113.A data bus may interconnect processor 111, memory 112, and communicationinterface 113. Communication interface 113 may be a network interfaceconfigured to support communication between data sharding computingplatform 110 and one or more networks (e.g., public network, privatenetwork, a local network, or the like). Memory 112 may include one ormore program modules having instructions that when executed by processor111 cause data sharding computing platform 110 to perform one or morefunctions described herein and/or one or more databases that may storeand/or otherwise maintain information which may be used by such programmodules and/or processor 111. In some instances, the one or more programmodules and/or databases may be stored by and/or maintained in differentmemory units of data sharding computing platform 110 and/or by differentcomputing devices that may form and/or otherwise make up data shardingcomputing platform 110. For example, memory 112 may have, store, and/orinclude data interception engine 112 a, data sharding engine 112 b,channel identification engine 112 c, and shard merging engine 112 d.Data interception engine 112 a may have instructions that direct and/orcause data sharding computing platform 110 to intercept, prior toreceipt of the transmission by the second computing device, the data, asdiscussed in greater detail below. Data sharding engine 112 b may haveinstructions that direct and/or cause data sharding computing platform110 to shard the data into a first shard and a second shard. In someembodiments, data sharding engine 112 b may have instructions thatdirect and/or cause data sharding computing platform 110 to determinethat a size of the data exceeds a threshold, and shard the data to limita size of each of the first shard and the second shard to less than thethreshold. Channel identification engine 112 c may have instructionsthat direct and/or cause data sharding computing platform 110 toidentify, within the communication network, a first communicationchannel and a second communication channel. In some embodiments, channelidentification engine 112 c may have instructions that direct and/orcause data sharding computing platform 110 to send, to the secondcomputing device, the first shard via the first communication channel,and the second shard via the second communication channel. Shard mergingengine 112 d may have instructions that direct and/or cause datasharding computing platform 110 to merge, the first shard and the secondshard, to reconfigure the data.

FIG. 2 depicts an illustrative network environment for data sharding fortransmission over a high generation cellular network in accordance withone or more example embodiments. Referring to FIG. 2 , data shardingcomputing platform 110 may detect, via a communication network,transmission of data 210 from a first computing device 205 to a secondcomputing device 230. As described herein, enterprise network managementinfrastructure 120 may be configured to manage, host, execute, and/orotherwise provide one or more enterprise applications. Network devices(e.g., first computing device 205, second computing device 230) withinenterprise network management infrastructure 120 may generate largevolumes of data transmissions, including machine-generatedtransmissions. For example, network devices, such as, various serversand/or databases, sensors, routers, computing devices, printers,scanners, cameras, and so forth, may generate vast amounts of data.Additional devices may include, for example, web resources, firewalls,and/or operating systems. Such data may include, for example, accessdata, log data, location data, data on software updates, diagnosticdata, user and/or account data, trading data, and so forth.

Generally, enterprise applications and/or vendor applications maycommunicate with one another to exchange information via datatransmissions. For example, each data transmission may originate at afirst computing device (e.g., first computing device 205) and a secondcomputing device (e.g., second computing device 230) may be an intendedrecipient. For example, a source application hosted by the firstcomputing device (e.g., first computing device 205) may initiate a datatransmission to request information, and the destination applicationhosted by the second computing device (e.g., second computing device230) may receive this request. In response, the destination applicationmay provide the requested information by initiating a data transmissionto the requesting (e.g., source) application. Data transmissions mayinclude exchange of data packets over a network. Content of the datatransmission may include electronic communication messages, HTMLdocuments, word processing documents, media content, audio and/or visualcontent, data packets associated with telecommunications, securedcommunications, and so forth.

In some embodiments, the source application and the destinationapplication may be associated with an enterprise organization. Forexample, the source application may be, for example, hosted by the firstcomputing device (e.g., first computing device 205), and the destinationapplication may be, for example, hosted by the second computing device(e.g., second computing device 230). In some embodiments, the sourceapplication may be associated with an enterprise organization, and thedestination application may be associated with an external vendororganization. For example, the source application may be, for example,hosted by the first computing device (e.g., first computing device 205),and the destination application may be, for example, hosted by anexternal computing device (e.g., second computing device 230). In someembodiments, the destination application may be associated with anenterprise organization, and the source application may be associatedwith an external vendor organization. For example, the sourceapplication may be, for example, hosted by an external computing device(e.g., first computing device 205), and the destination application maybe, for example, hosted by the second computing device (e.g., secondcomputing device 230).

In some embodiments, data sharding computing platform 110 may act as adata clearinghouse. For example, data sharding computing platform 110may intercept data 210. In some embodiments, data 210 may be interceptedin transit. For example, data sharding computing platform 110 mayintercept, prior to receipt of the transmission by the second computingdevice 230, data 210. Also, for example, data packets sent over anetwork may include headers that list source and/or destination networknodes for a data packet, a communication path for the data packet, andso forth. In some embodiments, data sharding computing platform 110 mayread the headers for data packets and intercept data that have headersindicating data management protocols. For example, a header may indicatethat data 210 is highly confidential, and data sharding computingplatform 110 may intercept the data to apply protective measures, asdescribed herein. As another example, a header may indicate that data210 is being transmitted by an enterprise employee with a high level ofsecurity clearance, and data sharding computing platform 110 mayintercept the data to apply appropriate protective measures.

In some embodiments, data sharding computing platform 110 may retrievethe data 210 from the first computing device 205, including a variety ofsources, such as, for example, via an application programming interface(“API”). In some embodiments, data sharding computing platform 110 maymonitor an enterprise device (e.g., first computing device 205) via adevice access manager, and/or device driver. Also, for example, data 210may be retrieved from log files (server log files, database log files,application activity files), network management devices, networkrouters, and so forth.

In some embodiments, data sharding computing platform 110 may determinethat a size of data 210 exceeds a threshold. For example, the size ofdata 210 may exceed a maximum capacity for a communication channel innetwork 220. Also, for example, data sharding computing platform 110 mayreceive network traffic information from a network management device,and determine that the size of data 210 may exceed a dynamic networkcapacity for network 220. In some embodiments, data sharding computingplatform 110 may perform load balancing activities to process the data210.

In some embodiments, data sharding computing platform 110 may shard thedata into a first shard and a second shard. For example, data shardingcomputing platform 110 may shard data 210 into a plurality of shards(e.g., shard 1 215(1), shard 2 215(2), . . . , shard N 215(N)). In someembodiments, data sharding computing platform 110 may shard data 210into a plurality of shards (e.g., shard 1 215(1), shard 2 215(2), . . ., shard N 215(N)) so as to limit a size of each of the shards to lessthan the threshold capacity for one or more communications channels ofnetwork 220.

The term “sharding” as utilized herein, may generally refer to a processof breaking a large data into smaller data. For example, in a tabularrepresentation of a large dataset, the dataset may be partitionedhorizontally. For example, a table with 1000 rows may be sharded into 10shards, each comprising 100 rows. For example, the shards may compriserows 1-100, rows 101-200, rows 201-300, . . . , and rows 901-1000.Generally speaking, shards need not be of the same size. For example, atable with 1000 rows may be sharded into three shards, a first shardcomprising rows 1-400, a second shard comprising rows 401-550, and athird shard comprising rows 551-1000. Similar techniques may be appliedto shard a database vertically.

In some embodiments, hash-based sharding may be performed. For example,data sharding computing platform 110 may generate a hash value from ashard key's value. The hash value may be utilized to allocate data tothe various shards. The hash value may then be utilized later torecombine the shards to reconfigure the dataset. In some embodiments,range-based sharding may be performed. For example, data shardingcomputing platform 110 may partition a range of data values and allocatedata to a shard based on an allocated range of data values. Additional,and/or alternative sharding techniques may be utilized to shard thedata.

Generally, with higher generation cellular networks (e.g., 5G andhigher), multiple channels may be available to transmit datasimultaneously over the network. For example, each cell in a servicearea may be equipped with multiple antennas configured to communicatewith devices within the cell so that multiple streams of data may besimultaneously transmitted, thereby increasing data transmission rates,reducing backlog due to network traffic, and enhancing speed andaccuracy of communications. In some embodiments, MIMO (Multiple-InputMultiple-Output) technology may be utilized. For example, MIMO isstandardized for various communication standards such as IEEE 802.11n(“Wi-Fi”), 802.11ac (“Wi-Fi”), WiMAX (“4G”), and Long Term Evolution(“LTE”). Also, for example, 5G NR (“New Radio”) Massive MIMO technologymay enable multi-channel data transmission by deploying a large numberof antennas, and utilizing complex algorithms that are designed toefficiently coordinate operations of such antennas. For example, spatialdiversity of Massive MIMO may enable data transmissions along multiplespatial paths.

In some embodiments, data sharding computing platform 110 may identify,within the communication network, a first communication channel and asecond communication channel. For example, data sharding computingplatform 110 may identify, within network 220, a first communicationchannel 220(1), a second communication channel 220(2), . . . , an N-thcommunication channel 220(N), In some embodiments, the communicationchannels may be identified based on a type and/or size of data shards(e.g., shard 1 215(1), shard 2 215(2), . . . , shard N 215(N)). Also,for example, the communication channels may be identified based on theirrespective availability.

In some embodiments, the communication channels may be over afifth-generation cellular network. For example, data sharding computingplatform 110 may identify the communication channels over thefifth-generation cellular network. A high generation cellular network,such as a fifth-generation cellular network, may be designed for highbandwidth, low latency, high data transmission rates, and/or locationaccuracies. As described herein, multipath propagation capabilities ofradio signals, such as MIMO capabilities of higher generation wirelessnetworks, may enable simultaneous communication channels that reducedelays due to high volume network traffic.

In some embodiments, the first communication channel may be associatedwith a first frequency for data transmission, and the secondcommunication channel may be associated with a second frequency for datatransmission. For example, millimeter wave bands, such as 26 GHz, 28GHz, 38 GHz, and 60 GHz, may provide data transmissions rates up to 20gigabits per second. In some embodiments, Massive MIMO, with typically64 to 256 antennas, may amplify such data transmissions rates. Standardsfor frequency bands for 5G NR and associated channel bandwidths may begenerally available. Frequency bands may also vary by geography (e.g.,different countries may implement different frequencies). For example, afrequency band in Europe may range from 3400 to 3800 MHz, whereas, USAmay provide frequency bands in the range 3100-3550 MHz and 3700-4200MHz. Also, for example, very high frequency bands may be available(e.g., Europe: 24.25-27.5 GHz, USA 27.5-28.35 GHz, and so forth).Accordingly, data sharding computing platform 110 may identifycommunication channels (e.g., a first communication channel 220(1), asecond communication channel 220(2), . . . , an N-th communicationchannel 220(N)), based on the shards (e.g., shard 1 215(1), shard 2215(2), . . . , shard N 215(N)). In some embodiments, availablecommunication channels may determine how data sharding computingplatform 110 may shard data 210 based on compatibility.

In some embodiments, data sharding computing platform 110 may send, tothe second computing device, the first shard via the first communicationchannel, and the second shard via the second communication channel. Forexample, data sharding computing platform 110 may send, to the secondcomputing device 230, shard 1 215(1) via first communication channel220(1), shard 2 215(2) via second communication channel 220(2), andshard N 215(N) via N-th communication channel 220(N).

In some embodiments, data sharding computing platform 110 may merge, thefirst shard and the second shard, to reconfigure the data. For example,data sharding computing platform 110 may merge shard 1 215(1) from firstcommunication channel 220(1), shard 2 215(2) from second communicationchannel 220(2), and shard N 215(N) from N-th communication channel220(N), to generate reconfigured data 225. Generally, reconfigured data225 may be substantially similar to data 210, subject to potentialvariations in network transmissions.

In some embodiments, adjacent shards may be merged together. Generally,two shards may be considered to be adjacent if a union of theirrespective sets of hash key ranges is a hash key range with no gaps. Forexample, a first shard with a first hash key range 232 . . . 254 and asecond shard with a second hash key range 255 . . . 282 may beconsidered as adjacent shards since a union of the first hash key range232 . . . 254 and the second hash key range 255 . . . 282 is acontiguous hash key range 232 . . . 282 without any gaps. On the otherhand, a first shard with a first hash key range 232 . . . 254 and asecond shard with a second hash key range 269 . . . 282 may not beconsidered as adjacent shards since a union of the first hash key range232 . . . 254 and the second hash key range 269 . . . 282 is not acontiguous hash key range, since it has a gap comprising a hash keyrange 255 . . . 268.

FIG. 3 depicts another illustrative network environment for datasharding for transmission over a high generation cellular network inaccordance with one or more example embodiments. Referring to FIG. 3 ,data sharding computing platform 110 may detect, via a communicationnetwork, transmission of encrypted data 310 from a first computingdevice 305 to a second computing device 350. For example, a first usermay generate a message at first computing device 305, for transmissionto second computing device 350. The message may be transmitted asencrypted data 310. As another example, a first user may generate arequest to trade shares via a trading platform operated by a financialinstitution. The request may be sent from first computing device 305 toan enterprise device 350 (e.g., a trading platform, or an enterprisedevice operated by an enterprise user). In such instances, a text of themessage or request may be converted to coded text or ciphertext.

Generally, trade related data may include confidential data. In someembodiments, trade related data may include publicly availableinformation such as live data from stock exchanges, sent via multi-cast.In some embodiments, data sharding computing platform 110 may separatethe confidential data from the non-confidential data, and may applyencryption techniques to encrypt the confidential data.

One or more encryption techniques may be utilized to encrypt data, suchas, for example, Advanced Encryption Standard (“AES”),Rivest-Shamir-Adleman (“RSA”), Triple Data Encryption Standard (“3DES”),Twofish, and so forth. Generally, an encryption process utilizes analgorithm to generate a pseudo-random encryption key. Although encrypteddata may be decrypted in an absence of the encryption key, computationalresources may pose a considerable challenge to such a decryptionprocess.

Generally, encrypted data and the encryption key may be transmittedtogether. However, transmitting the encrypted data separate from theencryption key may reduce a risk of intercepted data being decrypted.Accordingly, data sharding computing platform 110 may shard encrypteddata 310 into key management data 315(1) and encrypted data 315(2). Insome embodiments, data sharding computing platform 110 may identify afirst communication channel 325 in a first network 320, and a secondcommunication channel 335 in a second network 330. In some embodiments,first network 320 may be the same as second network 330. However, insome implementations, first network 320 may be a private network of anenterprise organization. For example, first network 320 may be a private5G network operated by a financial institution. Likewise, in someimplementations, second network 330 may be a public 5G network.

In some embodiments, data sharding computing platform 110 may send keymanagement data 315(1) via first communication channel 325, and sendencrypted data 315(2) via second communication channel 335. For example,data sharding computing platform 110 may send the encryption key via aprivate 5G channel, and send the encrypted data via the public 5Gchannel. In addition to separating transmission of the encryption keyfrom the encrypted data, which may reduce a risk of interception intransit leading to a potential decryption and unauthorized access of theencrypted data, sending the encryption key via a private network (e.g.,private 5G network), further reduces a risk of unauthorized access tothe encryption key.

In some embodiments, when confidential data is encrypted, data shardingcomputing platform 110 may send key management data 315(1) via firstcommunication channel 325, and send encrypted data 315(2) via secondcommunication channel 335. Additionally, a non-confidential portion ofthe data may be transmitted via a third communication channel (not shownin FIG. 3 ).

Also, as described herein, data sharding computing platform 110 maymerge, key management data 315(1) and the encrypted data 315(2), toreconfigure the data and generate reconfigured data 340. Generally,reconfigured data 340 may be substantially similar to encrypted data310. Such reconfigured data 310 may then be provided to second computingdevice 350.

FIG. 4 depicts an illustrative method for data sharding for transmissionover a high generation cellular network in accordance with one or moreexample embodiments. Referring to FIG. 4 , at step 405, a computingplatform having at least one processor, and memory may detect, via acommunication network, transmission of data from a first computingdevice to a second computing device. At step 410, the computing platformmay intercept, prior to receipt of the transmission by the secondcomputing device, the data. At step 415, the computing platform maydetermine if a size of the data exceeds a threshold. Upon adetermination that the size of the data exceeds a threshold, the processmoves to step 420. At step 420, the computing platform may shard thedata such that a size of each shard meets the threshold. At step 425,the computing platform may identify, within the communication network, aseparate communication channel for each shard. At step 430, thecomputing platform may send separate shards via the separatecommunication channels. At step 435, the computing platform may mergethe shards to reconfigure the data.

FIG. 5 depicts another illustrative method for data sharding fortransmission over a high generation cellular network in accordance withone or more example embodiments. Referring to FIG. 5 , at step 505, acomputing platform having at least one processor, and memory may detect,via a communication network, transmission of data from a first computingdevice to a second computing device. At step 510, the computing platformmay intercept, prior to receipt of the transmission by the secondcomputing device, the data. At step 515, the computing platform maydetermine if the data is in encrypted form. Upon a determination thatthe data is in encrypted form, the process moves to step 530. At step530, the computing platform may shard the data into a first shardcomprising the encrypted data, and a second shard comprising theencryption key management data. Subsequently, the process moves to step525.

Upon a determination that the data is not in encrypted form, the processmoves to step 520. At step 520, the computing platform may determine ifa size of the data exceeds a threshold. Upon a determination that thesize of the data exceeds a threshold, the process moves to step 525. Atstep 525, the computing platform may shard the data such that a size ofeach shard meets the threshold. At step 535, the computing platform mayidentify, within the communication network, a separate communicationchannel for each shard. At step 540, the computing platform may sendseparate shards via the separate communication channels. At step 545,the computing platform may merge the shards to reconfigure the data.

One or more aspects of the disclosure may be embodied in computer-usabledata or computer-executable instructions, such as in one or more programmodules, executed by one or more computers or other devices to performthe operations described herein. Generally, program modules includeroutines, programs, objects, components, data structures, and the likethat perform particular time-sensitive tasks or implement particularabstract data types when executed by one or more processors in acomputer or other data processing device. The computer-executableinstructions may be stored as computer-readable instructions on acomputer-readable medium such as a hard disk, optical disk, removablestorage media, solid-state memory, RAM, and the like. The functionalityof the program modules may be combined or distributed as desired invarious embodiments. In addition, the functionality may be embodied inwhole or in part in firmware or hardware equivalents, such as integratedcircuits, application-specific integrated circuits (ASICs), fieldprogrammable gate arrays (FPGA), and the like. Particular datastructures may be used to more effectively implement one or more aspectsof the disclosure, and such data structures are contemplated to bewithin the scope of computer executable instructions and computer-usabledata described herein.

Various aspects described herein may be embodied as a method, anapparatus, or as one or more computer-readable media storingcomputer-executable instructions. Accordingly, those aspects may takethe form of an entirely hardware embodiment, an entirely softwareembodiment, an entirely firmware embodiment, or an embodiment combiningsoftware, hardware, and firmware aspects in any combination. Inaddition, various signals representing data or events as describedherein may be transferred between a source and a destination in the formof light or electromagnetic waves traveling through signal-conductingmedia such as metal wires, optical fibers, or wireless transmissionmedia (e.g., air or space). In general, the one or morecomputer-readable media may be and/or include one or more non-transitorycomputer-readable media.

As described herein, the various methods and acts may be operativeacross one or more computing servers and one or more networks. Thefunctionality may be distributed in any manner, or may be located in asingle computing device (e.g., a server, a client computer, and thelike). For example, in alternative embodiments, one or more of thecomputing platforms discussed above may be combined into a singlecomputing platform, and the various functions of each computing platformmay be performed by the single computing platform. In such arrangements,any and/or all of the above-discussed communications between computingplatforms may correspond to data being accessed, moved, modified,updated, and/or otherwise used by the single computing platform.Additionally or alternatively, one or more of the computing platformsdiscussed above may be implemented in one or more virtual machines thatare provided by one or more physical computing devices. In sucharrangements, the various functions of each computing platform may beperformed by the one or more virtual machines, and any and/or all of theabove-discussed communications between computing platforms maycorrespond to data being accessed, moved, modified, updated, and/orotherwise used by the one or more virtual machines.

Aspects of the disclosure have been described in terms of illustrativeembodiments thereof. Numerous other embodiments, modifications, andvariations within the scope and spirit of the appended claims will occurto persons of ordinary skill in the art from a review of thisdisclosure. For example, one or more of the steps depicted in theillustrative figures may be performed in other than the recited order,and one or more depicted steps may be optional in accordance withaspects of the disclosure.

What is claimed is:
 1. A computing platform, comprising: at least oneprocessor; and a non-transitory computer-readable medium storingcomputer-readable instructions that, when executed by the at least oneprocessor, cause the computing platform to: detect, via a communicationnetwork, transmission of data from a first computing device to a secondcomputing device; intercept, prior to receipt of the transmission by thesecond computing device, the data; shard the data into a first shard anda second shard, wherein the sharding comprises: determining that a sizeof the data exceeds a threshold; and sharding the data to limit a sizeof each of the first shard and the second shard to less than thethreshold; identify, within the communication network, a firstcommunication channel and a second communication channel; send, to thesecond computing device: the first shard via the first communicationchannel, and the second shard via the second communication channel; andmerge, the first shard and the second shard, to reconfigure the data,wherein the transmission of data comprises encrypted data, and whereinthe first shard comprises the encrypted data, and wherein the secondshard comprises encryption key management data associated with theencrypted data.
 2. The computing platform of claim 1, wherein the datacomprises trading data, and wherein the instructions to shard the datacomprise additional computer-readable instructions that, when executedby the at least one processor, cause the computing platform to:identify, from the trading data, non-confidential data and confidentialdata; identify, within the communication network, a third communicationchannel; encrypt the confidential data; and wherein the encrypted datacomprises the encrypted form of the confidential data, and wherein theinstructions to send the data comprise additional computer-readableinstructions that, when executed by the at least one processor, causethe computing platform to: send the non-confidential data via the thirdcommunication channel.
 3. The computing platform of claim 1, wherein thefirst communication channel is over a private enterprise network, andthe second communication channel is over a public network.
 4. Thecomputing platform of claim 1, wherein the first communication channeland the second communication channel are over a fifth-generationcellular network.
 5. The computing platform of claim 4, wherein thefirst communication channel is associated with a first frequency fordata transmission, and the second communication channel is associatedwith a second frequency for data transmission.
 6. The computing platformof claim 4, wherein the first communication channel is over a privateenterprise network of the fifth-generation cellular network, and thesecond communication channel is over a public network of thefifth-generation cellular network.
 7. The computing platform of claim 4,further comprising a transceiver, and wherein the instructions to send,to the second computing device, the first shard and the second shard,comprise additional computer-readable instructions that, when executedby the at least one processor, cause the computing platform to: prior tosending the first shard and the second shard, configure the transceiverto convert the first shard and the second shard into a format compatiblewith data transmission over the cellular network.
 8. A method,comprising at a computing platform comprising at least one processor,and memory: detecting, via a communication network, transmission ofencrypted data from a first computing device to a second computingdevice; intercepting, prior to receipt of the transmission by the secondcomputing device, the encrypted data; sharding the encrypted data into afirst shard comprising encryption traffic, and a second shard comprisingencryption key management traffic, wherein the sharding comprises:determining that a size of the data exceeds a threshold; and shardingthe data to limit a size of each of the first shard and the second shardto less than the threshold; identifying, within the communicationnetwork, a first communication channel and a second communicationchannel; sending, to the second computing device: the first shard viathe first communication channel, and the second shard via the secondcommunication channel; merging, the first shard and the second shard, togenerate the encrypted data; and prior to sending the first shard andthe second shard, configuring a transceiver to convert the first shardand the second shard into a format compatible with data transmissionover a cellular network.
 9. The method of claim 8, wherein the firstcommunication channel and the second communication channel are over afifth-generation cellular network.
 10. The method of claim 8, whereinthe first communication channel is associated with a first frequency fordata transmission, and the second communication channel is associatedwith a second frequency for data transmission.
 11. The method of claim8, wherein the first communication channel is over a private network ofa fifth-generation cellular network, and the second communicationchannel is over a public network of the fifth-generation cellularnetwork.
 12. The method of claim 8, wherein detecting the transmissionof the encrypted data comprises detecting transmission of datacomprising non-confidential data and confidential data, and the methodfurther comprises: identifying, within the communication network, athird communication channel; encrypting the confidential data, whereinthe encryption traffic comprises the encrypted form of the confidentialdata; and sending the non-confidential data via the third communicationchannel.
 13. The method of claim 8, wherein the first communicationchannel and the second communication channel are over a fifth-generationcellular network and wherein the computing platform comprises atransceiver, the method further comprising: prior to sending the firstshard and the second shard, configuring the transceiver to convert thefirst shard and the second shard into a format compatible with datatransmission over the fifth-generation cellular network.
 14. One or morenon-transitory computer-readable media storing instructions that, whenexecuted by a computing platform comprising at least one processor, andmemory, cause the computing platform to: detect, via a communicationnetwork, transmission of data from a first computing device to a secondcomputing device, wherein the communication network is afifth-generation cellular network; intercept, prior to receipt of thetransmission by the second computing device, the data; shard the datainto a first shard and a second shard, wherein the sharding comprises:determining that a size of the data exceeds a threshold; and shardingthe data to limit a size of each of the first shard and the second shardto less than the threshold; identify, within the communication network,a first communication channel and a second communication channel; send,to the second computing device: the first shard via the firstcommunication channel, and the second shard via the second communicationchannel; and merge, the first shard and the second shard, to reconfigurethe data, wherein the transmission of data comprises encrypted data, andwherein the first shard comprises the encrypted data, and wherein thesecond shard comprises encryption key management data associated withthe encrypted data.
 15. The one or more non-transitory computer-readablemedia of claim 14, wherein the first communication channel is over aprivate enterprise network, and the second communication channel is overa public network.
 16. The one or more non-transitory computer-readablemedia of claim 14, wherein the data comprises trading data, and whereinthe instructions to shard the data comprise additional instructionsthat, when executed by the at least one processor, cause the computingplatform to: identify, from the trading data, non-confidential data andconfidential data; identify, within the communication network, a thirdcommunication channel; encrypt the confidential data; and wherein theencrypted data comprises the encrypted form of the confidential data,and wherein the instructions to send the data comprise additionalinstructions that, when executed by the at least one processor, causethe computing platform to: send the non-confidential data via the thirdcommunication channel.
 17. The one or more non-transitorycomputer-readable media of claim 14 wherein the first communicationchannel and the second communication channel are over thefifth-generation cellular network, wherein the computing platformcomprises a transceiver, and wherein the instructions that, whenexecuted by the computing platform comprising the at least oneprocessor, and the memory, cause the computing platform to: prior tosending the first shard and the second shard, configure the transceiverto convert the first shard and the second shard into a format compatiblewith data transmission over the fifth-generation cellular network.